Musical composition recognition method and system, storage medium where musical composition program is stored, commercial recognition method and system, and storage medium where commercial recognition program is stored

ABSTRACT

A playlist generating method for generating a playlist of content from received broadcasted data is provided. The playlist generating method includes the steps of: extracting features of broadcast content beforehand, storing the features in a content feature file, and storing information relating to the broadcast content in a content information DB; extracting features from the received data, and storing the features in a data feature file; searching for broadcast content of a predetermined kind by comparing data in the content feature file and data in the data feature file; when a name of the predetermined kind of content is determined, storing data corresponding to the broadcast content of the predetermined kind in a search result file; generating a playlist for the broadcast content of the predetermined kind from the search result file and the content information DB.

TECHNICAL FIELD

[0001] The present invention relates to a music recognizing method,system and a recording medium storing a music recognizing program. Moreparticularly, the present invention relates to a music recognizingmethod, system and a recording medium storing music recognizing programfor recognizing and storing, in real time, a name of broadcasted musicfrom images or voice information that is broadcasted on TV or FM and thelike.

[0002] In addition, the present invention relates to a CM (commercial)recognizing method and system and a recording medium storing a CMrecognizing program. More particularly, the present invention relates toa CM recognizing method, system and a recording medium storing a CMrecognizing program for recognizing and storing, in real time,broadcasted CM from images or voice information broadcasted on TV or FMand the like.

BACKGROUND ART

[0003] Conventionally, there is no system for recognizing a music nameused in content of image information or music information broadcasted inreal time, and storing the music name in a storage.

[0004] In addition, there is no apparatus for recognizing and storing aCM broadcasted in real time. In addition, there is no system forcomparing and recognizing CM data only by using CM information separatedat predetermined intervals.

[0005] As mentioned above, according to the conventional system, thereis no technique to monitor broadcasted music, so that the music namecannot be stored in a storage with time information when the music isbroadcasted. The time information can be assigned to a music name onlyby manually, so that the name of the broadcasted music and thebroadcasted time information cannot be provided in real time.

[0006] In addition, as to CM, there is no apparatus for recognizing andstoring a broadcasted CM from broadcasted images or voice information inreal time. This can be performed manually, so that there is a limit forreal time capability and expansion of scale.

DISCLOSURE OF THE INVENTION

[0007] The present invention is contrived in consideration of theabove-mentioned problems. An object of the present invention is toprovide a playlist generating technique for recognizing and storing amusic name of broadcasted music from images and voice information thatare broadcasted on TV and FM and the like.

[0008] Another object of the present invention is to provide a playlistgenerating technique for comparing and recognizing target music data inreal time without tag information or watermark information, not only fordata on the air but also for broadcasted data of streaming viacommunication network such as the Internet.

[0009] Further, an object of the present invention is to provide a CMrecognizing technique for recognizing and storing broadcasted. CM inreal time from images and voice information on the air on TV and FM andthe like.

[0010] The above object can be achieved by a playlist generating methodfor generating a playlist of content from received data, the playlistgenerating method including the steps of:

[0011] extracting features of content beforehand, storing the feature ina content feature file, and storing information relating to the contentin a content information DB;

[0012] extracting features from the received data, and storing thefeatures in a data feature file;

[0013] searching for content by comparing data in the content featurefile and data in the data feature file;

[0014] when the data in the content feature file matches the data in thedata feature file, data corresponding to the matched data is stored in asearch result file; and

[0015] generating a playlist for the content from the search result fileand the content information DB.

[0016] According to the present invention, the time-series playlist canbe generated automatically from broadcasted data on the air and thelike. The data feature file is, for example, a broadcast feature file.

[0017] In the above configuration, the method may further includes thestep of, when data in the data feature file is not included in thecontent feature file, registering the data in the content feature file.

[0018] According to the present invention, data can be automaticallyregistered to the content feature file.

[0019] The method may further include the steps of:

[0020] making content corresponding to the data that is not included inthe content feature file to be watched or listened to by a person; and

[0021] registering information relating to the content in the contentinformation DB.

[0022] According to the present invention, information relating to datain the content feature file that is automatically registered can beregistered. By using the registered information, the time-seriesplaylist can be automatically generated.

[0023] The method may further include the steps of:

[0024] when data in the data feature file is not included in the contentfeature file, making content corresponding to the data to be watched orlistened to by a person;

[0025] adding the content to the playlist with information related tothe content.

[0026] According to the present invention, the time-series playlist canbe complemented, so that more accurate playlist can be generated.

[0027] The above object can be also achieved by a music recognizingmethod for recognizing music from received data, the method includingthe steps of:

[0028] extracting features of music content beforehand, storing thefeatures in a content feature file;

[0029] extracting features from the received data, and storing thefeatures in a broadcast feature file;

[0030] searching for music by comparing data in the content feature fileand data in the broadcast feature file;

[0031] when a music name is determined, the music name is stored in asearch result file; and

[0032] generating a playlist of music from the search result file.

[0033] According to the present invention, the time-series playlist onmusic can be automatically generated.

[0034] The method may further include the steps of:

[0035] determining whether the received data is music or not;

[0036] if the data is music, storing information indicating that thedata is music and the time when the data is received in a musicextracted file;

[0037] if a music name for data in the broadcast feature file is notdetermined in the step of searching for music, storing the data in amusic name not-extracted file; and

[0038] generating a music not-detected file from the broadcast featurefile, the music extracted file and the music name not-extracted file.

[0039] According to the present invention, data that is music but notincluded in the time-series playlist can be grasped.

[0040] The method may further include the steps of:

[0041] making the music stored in the music not-detected file to belistened to by a person;

[0042] adding a music name and time of the music stored in the musicnot-detected file in the playlist.

[0043] According to the present invention, the time-series playlist canbe complemented, so that more accurate playlist can be generated.

[0044] The method may include the step of generating the time-seriesplaylist by using the search result file and the content information DBincluding information associated with the music name,

[0045] wherein the time-series playlist includes time, a name of musicbroadcasted at the time and information related to the name.

[0046] According to the present invention, the time-series playlistincluding a music name and information relating to the music name can begenerated automatically.

[0047] The method may include the steps of:

[0048] receiving broadcasted data in a plurality of areas;

[0049] sending data received in each area to a center system;

[0050] generating the time-series playlist by using the musicrecognizing method in the center system.

[0051] According to the present invention, the time-series playlistrelating to content broadcasted in broadcasting stations in each areacan be generated automatically.

[0052] The above object can be also achieved by a music recognizingmethod for recognizing music from received data, the method includingthe steps of:

[0053] extracting features of music content beforehand, storing thefeatures in a content feature file;

[0054] receiving broadcasted data in a plurality of areas;

[0055] extracting features from the received data, and sending thefeatures as data of a broadcast feature file to a center system in eacharea;

[0056] in the center system, searching for music by comparing data inthe content feature file and data in the broadcast feature file;

[0057] if a music name is determined, the music name is stored in asearch result file; and

[0058] generating a playlist of music from the search result file.

[0059] According to the present invention, since the broadcast featurefile is generated in each area and is sent to the center, transmissionamount to the center can be decreased.

[0060] In the music recognizing method, each of the content informationDB and the information related to the music name includes informationrelated to a CM, and the information related to the CM in the contentinformation DB is registered in the content information DB beforehand bythe CM recognizing method, the CM recognizing method further includingthe steps of:

[0061] detecting CM data from the received data;

[0062] extracting features of the CM data, and storing the features inthe broadcast feature file;

[0063] performing data comparison between the broadcast feature file anda master CM content feature file in which features of CM content arestored beforehand; and

[0064] if data in the broadcast feature file does not exist in themaster CM content feature file, registering the data in the master CMcontent feature file included in the content information DB as a new CM.

[0065] According to the present invention, the time-series playlistincluding CM information can be generated.

[0066] The above object can be also achieved by a CM recognizing methodfor recognizing a CM from received data, and storing recognized CM data,the method including the steps of:

[0067] detecting CM data from the received data;

[0068] extracting features of the CM data, and storing the features in abroadcast feature file;

[0069] performing data comparison between the broadcast feature file anda master CM content feature file in which features of CM content arestored beforehand; and

[0070] if data in the broadcast feature file does not exist in themaster CM content feature file, registering the data in the master CMcontent feature file as a new CM.

[0071] According to the present invention, CM monitoring which wasconventionally performed manually can be performed automatically, sothat CM data applicable foe generating the time-series playlist can beprovided.

[0072] In the CM recognizing method, the step of detecting the CM datafrom the received data may include the step of detecting a start pointand an end point of the CM data,

[0073] wherein, when the features of the CM data are extracted, a partof the CM data is cut out to a predetermined length, such that a lengthfrom the center of the CM data to an end is the same as a length fromthe center to another end.

[0074] According to the present invention, input error of the CM datacan be absorbed.

[0075] The method may further include the steps of:

[0076] displaying CM data that does not exist in the master CM contentfeature file as a result of the data comparison; and

[0077] registering information relating to the CM data in each databasein a CM management database group including the master CM contentfeature file.

[0078] According to the present invention, information relating to CMdata that is automatically registered can be registered in the master CMcontent feature file. By using this information, the time-seriesplaylist including information on CM can be generated.

[0079] Other objects, features and advantages of the present inventionwill become more apparent from the following detailed description whenread in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0080]FIG. 1 is a figure for explaining the principle of the presentinvention;

[0081]FIG. 2 shows the principle configuration of the present invention;

[0082]FIG. 3 shows an outline of a music recognizing system of thepresent invention;

[0083]FIG. 4 is a flowchart showing an outline of the operation of themusic recognizing system of the present invention;

[0084]FIG. 5 is a figure showing an outline of the CM recognizing systemof the present invention;

[0085]FIG. 6 is a (first) flowchart showing an outline of the operationof the CM recognizing system of the present invention;

[0086]FIG. 7 is a (second) flowchart showing an outline of the operationof the CM recognizing system of the present invention;

[0087]FIG. 8 shows an outline of the music recognizing system of thefirst example of the present invention;

[0088]FIG. 9 shows a flowchart of the music recognizing system of thefirst example of the present invention;

[0089]FIG. 10 shows an application example of the first example of thepresent invention;

[0090]FIG. 11 shows each file used when a time-series playlist isgenerated and relationships among them;

[0091]FIG. 12 is a figure for explaining attribute information in thetime-series playlist;

[0092]FIG. 13 is a figure for explaining attribute information in thetime-series playlist;

[0093]FIG. 14 shows an outline of a CM recognizing system of the secondexample of the present invention;

[0094]FIG. 15 is a figure for explaining a cutting method for extractingfeatures of CM data;

[0095]FIG. 16 shows a system configuration in the third example of thepresent invention;

[0096]FIG. 17 is a flowchart showing operation outline of the systemshown in FIG. 16;

[0097]FIG. 18 is a flowchart showing the operation of the system in thethird example of the present invention;

[0098]FIG. 19 shows a storing method of music data;

[0099]FIG. 20 shows a storing method of CM data;

[0100]FIG. 21 shows processes for generating the content feature filefrom the music/CM not-extracted file.

PREFERRED EMBODIMENTS FOR CARRYING OUT THE INVENTION First Embodiment

[0101]FIGS. 1 and 2 show the principle of the present embodiment.

[0102] As shown in FIG. 1, in this embodiment, features of content areextracted beforehand, and the features are stored in a content featurefile (step 1). A feature of received data is extracted and the featureis stored in a broadcast feature file (step 2). Music is searched for bycomparing data of the content feature file and data of the broadcastfeature file (step 3). When the music is searched for, information onthe music is stored in a search result file (step 4). Then, atime-series playlist of music is generated from the search result fileand is stored (step 5).

[0103] As shown in FIG. 2, the principle configuration of the musicrecognizing system of the present embodiment includes a contentgenerating means 300 for generating content beforehand, extracting thefeatures of music content and storing the features in a content featurefile 320, a feature extracting means 105 for extracting a feature ofreceived data and storing it in a broadcast feature file 140, a musicsearch means 120 for searching for music by comparing data of thecontent feature file 320 and the broadcast feature file 140 and storingthe search result in a search result file 150, and a list generatingmeans 200 for generating a time-series playlist from the search resultfile 150 and storing it.

[0104]FIG. 3 shows an outline of the music recognizing system of thepresent invention. The system shown in the figure includes an on-aircapture/search apparatus 100, a music recognizing/registering apparatus200, and a content generating apparatus 300. These apparatuses arerealized by PCs and the like. Although the present system can berealized by one PC that includes the functions of the present invention,the system includes the three apparatuses in consideration of processloads of PC, performance cost, specification of current hardware and thelike in the embodiment of the present invention.

[0105] The on-air capture/search apparatus 100 includes an on-aircapture part 110, a search part 120, a music extracted file 130, abroadcast feature file 140, a search result file 150, a music namenot-extracted file 160, a music not-detected file 170, and a time dataproviding part 180.

[0106] The on-air capture part 110 successively monitors broadcasteddata from TV, radio broadcasting station, determines whether themonitored broadcasted data is music or non-music. When the data ismusic, the on-air capture part 110 records that the broadcasted data atthe time of monitoring is music in the music extracted file 130, andextracts the feature of the broadcasted data in real time at intervalsof 7.5 seconds, and stores the features in the broadcast feature file140. In addition, the music is stored as digital data in a file (notshown in the figure) at intervals of 7.5 seconds. The on-air capturepart 110 performs the above-mentioned processes on the basis of timeinformation from the time data providing part 180. In addition, timestamp is provided to the captured information and the capturedinformation is stored with the time stamp.

[0107] As for the reason for using the interval of 7.5 seconds fordetecting music in a CM, since the time length of a CM is 15 seconds atthe minimum currently, the search of music data can be performed withreliability by using a half of the length as the search interval.

[0108] The determination whether music or non-music in the on-aircapture part 110 can be realized by using a conventional technology fordetermining whether music or non-music (for example, talk and the like),for example, the conventional technology is “Gakuran” (music/non-musicdetection technology) : Japanese patent application No. 8-340293,Japanese patent application No. 10-68158 and the like. The on-aircapture part 110 registers information indicating that the data isdetermined to be music in the music extracted file 130 by using thetechnology.

[0109] The search part 120 reads, in a memory, the file in whichfeatures of content generated by the content generating apparatus 300,and reads the broadcast feature file 140. Then, the search part 120performs matching between the two files and stores the result ofmatching in the search result file 150. Data that does not succeed inthe matching is stored in the music name not-extracted file 160.

[0110] As for the above-mentioned search by matching, a learning activesearch method that is described in Japanese patent No. 3065314 “Highspeed signal search method, apparatus and recording medium” can be used.In this method, a similarity value between data of the content featurefile and data in the broadcast feature file, and the similarity value iscompared with a threshold, so that the search is performed. The Japanesepatent No. 3065314 can be referred to for the details of the searchmethod.

[0111] The music extracted file 130 includes data of the informationindicating music with a time stamp. The broadcast feature file that isgenerated by the on-air capture part 110 is a TAZ file (binary file).The TAZ file is a file that enables high speed comparison in thelearning active search.

[0112] The broadcasted content is stored in a WAV file and the like (notshown in the figure).

[0113] The on-air capture part 110 automatically captures broadcasteddata on the air, and feature data of the broadcasted data is stored inthe broadcast feature file 140.

[0114] Data that is music but that is not detected as music by matchingis extracted from the music extracted file 130, the music namenot-extracted file 160 and the broadcast feature file 140, and the datais stored in the music not-detected file 170.

[0115] The search result file 150 stores the result of matching betweenthe content feature file (after mentioned) generated by the contentgenerating apparatus 300 and the broadcast feature file 140. That is, asa result of matching, information (music name and the like)corresponding to matched data is stored in the search result file, and apiece of data of the broadcast feature file 140 that does not exist inthe content feature file is stored in the music name not-extracted file(after mentioned).

[0116] The music checking/registering apparatus 200 includes a musicchecking part 210 and a registering part 220, and outputs thetime-series playlist 230.

[0117] The music checking part 210 extracts time, music name, artist,program (CM) name, client, product, talent, CD information and the likecorresponding to recognized music by using the search result file 150and the content information DB 330, and passes them to the registeringpart 220.

[0118] The registering part 220 registers information extracted by themusic checking part 210 in the time-series playlist file 230 in theorder of time.

[0119] In addition, an operator checks broadcasted content stored in themusic not-detected file by using the music checking/registeringapparatus 200, so that the music is recognized and the data is added tothe time-series playlist. The operator listens to the music on the basisof time information in the music not-detected file in which the music iscaptured by the on-air capture part 110 in the form of WAV file and thelike, so that the operator can recognize the broadcasted content.

[0120] The content generating apparatus 300 includes a contentgenerating part 310, a content feature file 320 and a contentinformation DB 330.

[0121] The content generating part 310 obtains content from a medium inwhich music is recorded, stores the music and attribute data that can beapplied to the content feature file 320 in the content informationdatabase 330. In addition, the content generating part 310 extracts thefeatures of the music, and stores the features in the content featurefile 320 with the music names.

[0122] The content feature file 320 is a file generated in the contentgenerating part 310, and stores music names and feature informationcorresponding to the music.

[0123] The content information DB 330 stores all attribute data of musicby the content generating part 310.

[0124] Next, the operation of the music recognizing system of thepresent invention will be described. FIG. 4 shows an outline of theoperation of the music recognizing system of the present invention.

[0125] Step 101) The content generating apparatus 300 registers musicand attribute data of the music from a recording medium and the like ofmusic content in the content information DB 330. The attribute data are,for example, music name, artist name, program name, client name, productname, talent name and the like.

[0126] Step 102) The content generating apparatus 300 extracts thefeatures of music and stores the features in the content feature file320.

[0127] The processes so far are pre-processes for following processes.

[0128] Step 103) The on-air capture/search apparatus 100 captures imagesor voices on the air. The “images or voices on the air” include imagesor voices broadcasted via the Internet.

[0129] Step 104) The on-air capture/search apparatus 100 determineswhether the captured broadcasted data is music or non-music by using atechnique for determining whether music/non-music.

[0130] Step 105) When the data is music in step 103, informationindicating that the broadcasted data at the time is music is recorded inthe music extracted file 130. “Recording information indicating that thebroadcasted data at the time is music” is, for example, providing a flagindicating music at the time.

[0131] Step 106) At the same time of the steps 104 and 105, the featureof the music is extracted at intervals of 7.5 seconds and the feature isstored in the broadcast feature file 140. In addition, broadcasted dataof music is stored in a file (not shown in the figure).

[0132] Step 107) Next, the on-air capture/search apparatus 100 launchesan application for searching for music, and reads information in thecontent feature file 320 that was generated by the content generatingapparatus in step 102 in a memory.

[0133] Step 108) The search part 120 of the on-air capture/searchapparatus 100 also reads.the broadcast feature file 140, and performsmatching between the two files. At this time, the before-mentionedlearning active search technology is used.

[0134] Step 109) The result of the matching is stored in the searchresult file 150. The feature data that fails in the matching is storedin the music name not-extracted file 160.

[0135] Step 110) Next, the music checking/registering apparatus 200reads each piece of data in the content information DB 330 from thecontent generating apparatus 300.

[0136] Step 111) In addition, the music checking/registering apparatus200 reads the search result file 150 from the on-air capture/searchapparatus 100.

[0137] Step 112) Accordingly, the music checking/registering apparatus200 extracts information such as music name, artist name, capturedprogram, client, product, talent and the like, from data in the searchresult file 150 and data in the content information DB 330, sorts thesepieces of information in time series, so as to generate a time seriesplaylist and stores it as the time series playlist DB 230.

[0138] Step 113) In addition, the operator checks the music namecorresponding to feature data stored in the music not-detected file bylistening to the music, so that the time series playlist iscomplemented.

Second Embodiment

[0139] Next, as the second embodiment of the present invention, a CMrecognizing system for recognizing and storing CM (commercial) frombroadcasted images or voice information on the air on TV or FM/AM willbe described. By referring to CM data generated by the CM recognizingsystem, a playlist that includes CM data can be generated from the musicrecognized in the first embodiment.

[0140]FIG. 5 shows an outline of the CM recognizing system of thepresent invention.

[0141] The CM recognizing system shown in the figure includes an on-aircapture/search apparatus 400, a CM checking/updating part 500 and a CMmanagement database group 600.

[0142] The on-air capture/search apparatus 400 includes a capture part410, a search part 420, an FM/AM-CM file 430, a broadcast feature file440, a CM data file 450 and a TV-CM file 460 and a time data providingpart 470.

[0143] The capture part 410 successively monitors broadcasted data onthe air from a TV or radio broadcasting station, determines whether thebroadcasted data is a CM or not by determining start and end of the CM.When the broadcasted data is a CM, the monitored CM data is stored inthe TV-CM file 460, or stored in the FM/AM-CM file 430. In addition, thecapture part 410 provides a time stamp to the CM data by using timeinformation provided from the time data providing part 470.

[0144] Further, the capture part 410 generates feature data of CM fromcaptured data and stores the feature data in the broadcast feature file440. As described later, when the feature file 440 is generated, inorder to absorb an error of cut points of data cut out by using startand end of the CM, the both ends of the CM data are cut out such thatboth lengths from the center to the ends are the same and the length ofthe reprocessed CM data becomes a constant length (8.0 seconds). Thereprocessed on-air data are processed into feature data by using thelearning active search technology, and the feature data is stored as theTAZ format. The TAZ file is a file that enables high speed comparisonprocessing in the learning active search.

[0145] The search part 420 reads, in the memory, the broadcast featurefile 440 and a file, in a master CM management database group 600, inwhich features of CM are stored. Then, the search part 420 performsmatching between the two files, and stores the matching result in the CMdata file 450. The search part 420 uses the learning active search(Japanese patent No. 3065314 and the like). In this case, as for cut-outCM data in which any CM can not be detected, as a matching result, theCM data is stored in the CM data file 450 in which on-air time isprovided as the name of the CM data.

[0146] The FM/AM-CM file 430 stores, as a file of WAV format (only voiceformat), CM data captured by the capture part 410 and that was on theair by FM/AM.

[0147] The broadcast feature file 440 stores feature data of the CMextracted from the CM data captured by the capture part 410. Inaddition, the broadcast feature file 440 is a TAZ file (binary file).

[0148] The TV-CM file 460 stores, as a file of AVI format, CM datacaptured by the capture part 410 that was broadcasted on TV.

[0149] The CM checking/updating part 500 reads the CM data file 450 thatstores CM data in which the CM name and the like is not determined.There is a high probability that the CM in the CM data file 450 is a newCM. Thus, the operator checks a newly registered CM, and extractssponsor (client), product name, music name, talent name and the like,and stores them in files of the CM management database group 600.

[0150] The CM management database group 600 includes a CM master 610, aproduct master 620, a talent master 630, a music name master 640, asponsor master 650, and a master CM content feature file 660. Data inthe product master 620, the talent master 630, the music name master640, the sponsor master 650, and the master CM content feature file 660are extracted by the CM checking/updating part 500. In addition, thesemasters are master files generated for each attribute of the CM datastored in the CM master 610.

[0151] Next, the operation of the above-configuration will be described.

[0152]FIGS. 6 and 7 shows flowcharts showing an outline of the operationof the CM recognizing system of the present invention.

[0153] Step 301) The capture part 410 of the onair capture/searchapparatus 400 captures broadcasted data on the air.

[0154] Step 302) The capture part 410 detects CM data from the capturedbroadcasted data, and extracts the feature by using the before-mentionedmethod from the CM data.

[0155] Step 303) The extracted feature is stored in the broadcastfeature file 440, and goes to step 307.

[0156] Step 304, 305) In addition to performing the above-mentionedprocesses, TV-CM is stored in the TV-CM file 460.

[0157] Step 306) In addition, when the extracted CM is a CM that was onthe air by FM/AM, the CM is stored in the FM/AM-CM file 430.

[0158] Step 307) After the step 303, the search part 420 reads, in thememory, the broadcast feature file 440 and the master CM content featurefile 660 of the CM management database group 600, and performs thelearning active search in which the two files are compared.

[0159] Step 308) By performing the search, if a CM is determined, theprocess goes to step 307, then, next search is performed for the data ofthe broadcast feature file 440 and the master CM content feature file660. If the CM is not determined, the process goes to the step 309.

[0160] Step 309) If a CM is not determined, the. data is registered inthe CM data file by providing on-air time as the name.

[0161] Step 310) The operator checks the CM registered in the CM datafile 450 by using a conventional software and the like by using the CMchecking/updating part 500.

[0162] Step 311) The operator performs maintenance of the CM master 610,and performs maintenance of masters for each attribute from the CMmaster 610.

[0163] Accordingly, a new CM can be registered in the database.

Third Embodiment

[0164] In the same way as the first embodiment in which the time seriesplaylist is generated from the recognized music, the time seriesplaylist can be generated from the CM recognized in the secondembodiment.

[0165] In addition, in the same way as the example of the CM in thesecond embodiment, it is possible to update the content feature file andcontent information DB of music.

[0166] Further, it is possible to update the content feature file andthe content information DB on CM or music in the same way as the secondembodiment while generating the time series playlist in the same way asthe first embodiment. The concrete example will be described later.

[0167] In the following, concrete examples for the above-mentionedembodiments will be described with reference to figures.

EXAMPLE (First Example) Corresponding to the First Embodiment

[0168]FIG. 8 shows a configuration of the music recognizing system ofthe first example of the present invention. In each apparatus shown inthe figure, the same numeral is assigned to the same part as that shownin FIG. 3, and the explanation will be omitted.

[0169]FIG. 9 shows a flowchart of the operation of the music recognizingsystem of the first example of the present invention. In the following,the music recognizing system of the present invention will be describedwith reference to FIGS. 8 and 9.

[0170] As shown in FIG. 8, the music recognizing system includes anon-air capture/search apparatus 100, a content generating apparatus 300and a music checking/registering apparatus 200 that are connected. Inthe on-air capture/search apparatus 100, a PC 110 for capturingbroadcasted data in real time and a PC 120 for searching the broadcastfeature file 140 are connected. The content generating apparatus 300includes a PC 310 for managing a content feature file 320 that storescontent features of music content and a content information DB 330. Themusic checking/registering apparatus 200 is for registering atime-series playlist to a DB.

[0171] In a processing system A shown in FIG. 9, the PC 110 capturescontent on the air (step 201), and outputs the broadcast feature file140 from the captured data at intervals of 7.5 seconds (step 202). Next,the PC 120 obtains data of the music content feature file 320 and thebroadcasted feature file 140 on the memory, and the PC 120 searches themfor music by using the learning active search (step 203), and outputs asearch result to the search result file 150 (step 205). At this time, ifthe music name is not determined by the search, the feature data isstored in the music name not-extracted file (step 207).

[0172] After the above-mentioned processes are completed, the musicchecking/registering apparatus 200 generates the time-series playlistfrom the search result of the search result file 150 and the contentinformation DB, and stores it in the DB 230.

[0173] In the processing system B shown in FIG. 9, the PC 110 in theon-air capture/search apparatus 100 determines whether the broadcasteddata is music or not (step 301). If the data is music, the PC 110outputs information indicating that the data is music and a time stampto the music extraction file 130 (step 302). In addition, the music isstored in a WAV file and the like (not shown in the figure) with thetime stamp.

[0174] Then, the music name not-extracted file 160 (processing system A)and the music extracted file 130 (processing system B) are merged, sothat the music name not-detected file 170 for each time can be output(steps 208, 209), and the data can be fed back to the search result file150 by the operator. Accordingly, the time-series playlist can becomplemented.

[0175] As for work of the operator, the operator complements necessarydata items to the search result file while the operator checks contentin the music not-detected file in the PC 120 for searching.

[0176] As the content feature file 320 and the broadcast feature file150, the TAZ file (binary file used for the learning active search) isused.

[0177] In the generation of the playlist, the search result file and thecontent information DB including CM master and the like are connected.As an concrete example, an application example will be described later.

[0178] In the example shown in FIG. 8, the PC 110 may capture thebroadcasted data of all parts of the country by receiving data from theparts of the country, so that the PC 110 can generate the broadcastfeature file. In addition, by placing the PC 110 in each part of thecountry, each PC 110 may capture broadcasted data at the place andgenerate a broadcast feature file and send the broadcast feature file tothe PC 120 placed in the center.

[0179] In the following, an application example of the present inventionwill be described.

[0180]FIG. 10 shows the application example of the example of thepresent invention.

[0181] In the figure, the content management center corresponds to thecontent generating apparatus shown in FIG. 8. The data centercorresponds to the on-air capture/search apparatus shown in FIG. 8.

[0182] First, the content management center obtains CDs and the like foraudition from record companies, buys DVDs and new CDs from CD shops andthe like. Then, in the content management center, contents are stored inthe content information DB 330 from the recording mediums withattributes of the contents. In addition, features of the contents areextracted and stored in the content feature file 320 (music database inthe example of FIG. 10).

[0183] Next, for example, the data center obtains, via a tuner,broadcasted content of TV (VHS) or FM and the like obtained via anantenna placed in all parts of the country, or the data center obtainsbroadcasted content obtained via a parabola antenna from satellitebroadcasting and the like. The data center digitizes the obtainedbroadcasted data at intervals of 7.5 seconds, and extracts features ofthe data, and stores the features in the broadcast feature file 140. Inaddition, the data center determines whether the data is music ornon-music such as talk and the like, and stores the result in the musicextracted file 130.

[0184] By using the search engine (leaning active search technique), thePC for searching in the data center searches for music from the contentfeature file and the broadcast feature file that are obtained beforehandfrom the content management center, and stores the result in the searchresult file 150.

[0185] Accordingly, the PC used as the music checking/registeringapparatus 200 in the data center generates a time-series playlist byusing the search result file and the content information DB 330. In theexample of FIG. 10, music name, artist, program (CM), client, product,talent, CD information and the like are registered in a database thatmay be used in a Web site and the like in the order of time (using timestamps provided to the search result file) as the time-series playlist.In addition, as for the music that is not searched for, the music isadded by the operator.

[0186]FIG. 11 shows each file used when the time-series playlist isgenerated, and relationships among them.

[0187] As shown in the figure, the search result file and the music namenot-extracted file are generated from the broadcast feature file and thecontent feature file. Then, the time-series playlist is generated fromthe search result file and the content information DB.

[0188] In addition, the music not-detected file is generated from themusic extracted file and the music name not-extracted file and the like.By checking the music name of the music recorded in the file by theoperator, the time-series playlist can be complemented. In addition, asfor the music in which the music name and the like is recognized, themusic can be added to the content feature file as necessary byextracting the feature of the music. Accordingly, when the musiccorresponding to TAZ 4 is captured, the music can be recognized afterthis.

[0189] Next, a method for generating the time-series playlist shown inFIG. 10 by using the content information DB will be described withreference to FIGS. 12 and 13.

[0190]FIG. 12 shows a case where each item is determined at 9 o'clock inthe playlist. As shown in the figure, the content information DBincludes various databases (master databases) associated with the TAZdata. Therefore, if a music name is determined from TAZ data, eachinformation at 9 o'clock can be obtained by pursuing from the voicesource master to each master. In addition, the program name can beobtained from the broadcasting station name and the time. Accordingly,the timeseries playlist that includes various related information can begenerated.

[0191]FIG. 13 shows a case when the time is 11:46. In the same waymentioned above, various information corresponding to the time can beobtained by using various masters from the TAZ data.

[0192] Next, a simulation result of the music recognizing system of thepresent invention will be described. In the simulation, actuary recordeddata of FM broadcasting (about 35 minutes) is used in which 7 pieces ofmusic are included as samples. In addition, 193 pieces of CD music areused as database samples in which 6 pieces of music are included in theabove-mentioned broadcasted samples.

[0193] As for conditions for the simulation, the broadcasted sample iscompared with all 193 pieces for each 7.5 seconds (193 pieces=about 20hours), in which the specification of the PC server is 1 CPU (PentiumXeon 933 MHz), 2 GB memory, Linux gcc 291.

[0194] As a result of the simulation in the above-mentioned conditions,the 6 pieces that should be detected were detected correctly, the timeerror was about within 7.5 seconds, and the search is completed in about45 seconds for the 35 minutes music (2100 seconds). This speed is about50 times (=2100/45) faster than the actual music speed. By using thisspeed, processes for about 9000 pieces of music can be expected inactual time.

[0195] In addition, although the above example is described on the basisof FIGS. 8 and 9, the process shown in FIG. 9 can be realized by aprogram, so that the program is stored in a disk apparatus connected toa computer used in the data center and the content management center, orin a portable recording medium such as a floppy disk and a CD-ROM. Then,when the present invention is executed, the program can be installed inthe PC used in the data center or the computer management center, sothat the present invention can be easily realized.

Example Corresponding to the Second Embodiment SECOND EXAMPLE

[0196] In this example, a CM is detected in real time from broadcasteddata that is being broadcasted, so that the CM is recognized and stored.As mentioned before, by using the thus stored CM data as theabove-mentioned master file, the time-series playlist includinginformation on the CM can be generated.

[0197]FIG. 14 shows a configuration of the CM recognizing system of thesecond example of the present invention. In the configuration elements,the same numeral is assigned to the same configuration part as that ofFIG. 5, and the explanation will be omitted.

[0198] In the CM recognizing system of this example, the CM recognizingsystem includes a capture PC part 410, an on-air capture/search part400, a CM checking/updating part 500, and a CM management database 600.The capture PC part 410 captures broadcasted content. The on-aircapture/search part 400 includes a learning active search PC 420 forcomparing the broadcast feature file 440 and a master CM content featurefile 660. The CM checking/updating part 500 is used for checking a CMand for updating processes. The CM management database 600 managesvarious master files of the CM.

[0199] In the following, the file format in FIG. 14 will be described.

[0200] The broadcast feature file 440 is a file of TAZ format in whichfeatures of both of TV-CM and FM/AM-CM extracted in real time arestored. The TV-CM file 460 is a file of AVI format in which TV-CM isstored, and the TV-CM file 460 is managed in pairs with content of thebroadcast feature file 440.

[0201] The FM/AM-CM file 430 is a file of WAV format in which FM/AM-CMis stored, and is managed in pairs with content of the broadcast featurefile 440.

[0202] The CM data file 450 is a file in which a CM to be newlyregistered is stored. When the CM is TV-CM, the data is stored as an AVIformat for example. When the CM is FM/AM-CM, the data is stored as a WAVformat.

[0203] The master CM content feature file in the CM management databasegroup 600 is stored as the TAZ format.

[0204] In the following, the operation in the above-mentionedconfiguration will be described with reference to FIGS. 6 and 7.

[0205] The capture PC 410 captures content on the air (step 301). Next,the capture PC 410 obtains the start and the end of the CM by using a CMdetection module. As a technique for the CM detection module, atechnique disclosed in Japanese patent application No. 6-312976 “imagecut point detection method and apparatus” (Tanimura, Tonomura) can beused.

[0206] Next, the cut-out CM data is reprocessed in which the CM data iscut-out into a predetermined length (8.0 seconds) such that the lengthfrom the center of the CM data to one end is the same as the length fromthe center to another end as shown in FIG. 15 in order to absorb anerror of cut points cut by the CM detection module. The feature of thereprocessed CM data is extracted as the broadcast feature (step 302),and the broadcast feature is stored in the broadcast feature file 440(step 303).

[0207] The capture PC 410 stores data on the air by using the CMdetection module (steps 304, 305 and 306). When the data on the air isTV, the data is stored as the AVI format, and when the data is FM/AM,the data is stored as the WAV format.

[0208] Next, the learning active search PC 420 reads the broadcastfeature file 440 and the master CM content feature file 660 of the CMmanagement database group 600 in the memory, so that the learning activesearch is performed (step 307). If a piece of data of the broadcastfeature file 440 is not registered in the CM content feature file 660,the corresponding CM is registered in the CM data file 450 (step 309).In addition, if the data in the broadcast feature file 440 is notregistered in the CM content feature file 660, the data is registered inthe master CM content feature file 660 unconditionally.

[0209] Next, checking of the CM registered in the CM data file 450 isperformed in the CM checking/updating part 500 (step 310). The checkingof the CM is performed by using an existing software. The CM is finallyregistered in the CM master 610 by adding various additional informationby the operator. Further, by using attributes of the CM registered inthe CM master 610, the product master 620, the talent master 630, themusic name master 640, the sponsor master 650, the master CM contentfeature file 660 are updated by corresponding data (step 311).

[0210] In the above-mentioned example, although the above example isdescribed on the basis of flowcharts in FIGS. 6 and 7, the process shownin FIG. 6 can be realized by a program, so that the program is stored ina disk apparatus connected to a computer used in the on-aircapture/search apparatus, or stored in a portable recording medium suchas a floppy disk and CD-ROM and the like. Then, when the presentinvention is executed, the program can be installed in the PC (capturePC, learning active search PC) used in the on-air capture/searchapparatus, so that the present invention can be easily realized.

[0211] In the above example, although processes are shown in whichbroadcasted data on the air from a broadcasting station of TV, FM/AM andthe like is captured, and recognized and stored, the present inventionis not limited to this example. The same processes as theabove-mentioned processes can be applied to data transmitted via acommunication network such as the Internet and the like.

[0212] In the above example, although the feature of the music isextracted at intervals of 7.5 seconds and the feature of CM is extractedat intervals of 8 seconds, these are merely examples and the presentinvention is not limited to these examples.

Example Corresponding to the Third Embodiment cl (THIRD EXAMPLE)

[0213] Next, an example will be described in which, while the playlistis generated in the same way as the first example by capturing music andCM, data is registered in the content generating part in the same way asthe second example.

[0214]FIG. 16 shows a system configuration in the third example.

[0215] As shown in FIG. 16, the music/CM recognizing system in the thirdexample includes a capture part/search apparatus 700, a contentgenerating apparatus 800, and a music/CM checking/registering apparatus900. The capture part/search apparatus 700 captures broadcasted contentand searches for music and CM. The content generating apparatus 800generates a content information DB. The music CM checking/registeringapparatus 900 generates the time-series playlist from the search resultfile and the content information DB, and registers attribute informationof newly recognized music and CM in the content generating apparatus800.

[0216] The on-air capture/search apparatus 700 includes an on-aircapture part 710, a search part 720, a music/CM extracted file 730, abroadcast feature file 740, a search result file 750, a music/CMnot-extracted file 760, a music/CM not-detected file 770, and a contentfeature file generating part 780. The content generating apparatusincludes a content generating part 780, a content feature file 820 and acontent information DB 830.

[0217]FIG. 17 is a flowchart showing outline operation of the systemshown in FIG. 16. The outline operation will be described with referenceto FIG. 17.

[0218] The content generating apparatus 800 extracts features of musicand CM, and stores the features as the content feature file (step 401).In the on-air capture/search apparatus 700, the on-air capture part 710captures broadcasted content including music and CM and stores thecontent as the AVI file, WAV file and the like, and extracts features ofthe content, and stores the feature in the broadcast feature file 740(step 402). Next, music and CM are searched for by using the contentfeature file 820 and the broadcast feature file 740 (step 403). When themusic or the CM is determined, information on the music or the CM isstored in the search result file (step 404), so that the time seriesplaylist is generated (step 405). If the music or the CM is notdetermined, the feature data by which the music or the CM is notdetermined is stored in the music/CM not-extracted file (step 406).Then, a content feature file corresponding to the music or the CM isgenerated, so that the content feature file is automatically registeredin the content feature file 820 in the content generating apparatus 800(step 407).

[0219] Next, the above-mentioned processes will be described in moredetail by using a flowchart of the processes in the on-air capturepart/search apparatus 700 shown in FIG. 18.

[0220] As shown in FIG. 18, the processes by the on-air capturepart/search apparatus 700 in this example can be divided into a processsystem 1 for performing search for music and CM, a process system 2 forperforming music detection, music determination and storing, and aprocess system 3 for performing CM detection and storing.

[0221] In the process system 2, in the same way as the first example, itis determined whether the broadcast content is music or not, a musicextracted file is generated, and music data is stored as a WAV file andthe like (steps 501-503). FIG. 19 shows a storing method of music data.Accordingly, the part determined to be music is stored at intervals of7.5 seconds.

[0222] In the process system 3, in the same way as the second example,the CM extracted file is generated by detecting cut points inbroadcasted data, and the CM data is stored as the AVI file and the like(steps 511-513). FIG. 20 shows the manner. Accordingly, the CM partbetween the cut points is stored.

[0223] The CM extracted file is similar to the music extracted file inmusic. In the CM extracted file, information indicating that the data isCM and the time are recorded.

[0224] In the process system 1, in the same way as the first example asfor music, and in the same way as the second example as for CM, thefeature is extracted and music or CM is searched for (steps 521, 522).

[0225] When a name of music or CM is determined, the search result file750 is generated (step 523). If the name of music or CM is notdetermined, the data is stored in the music/CM not-extracted file (step524), and the content feature file is automatically generated by usingthe data (step 525), so as to be provisionally registered in the contentfeature file 520.

[0226]FIG. 21 shows processes for generating the content feature filefrom the music/CM not-extracted file. Accordingly, the content featurefile is generated from data files (AVI or WAV) of music or CMcorresponding to data in the music/CM not-extracted file.

[0227] In the same way as the first example, the music/CM not-detectedfile is generated from the music/CM not-extracted file and the music/CMextracted file and the like (step 526). The operator checks the music orthe CM and the time-series playlist is complemented by the recognizedmusic or CM (step 527). Further, by using the result of checking,various databases in the content generating apparatus are updated (musicname, artist name and the like are associated with a TAZ file), so thatthe provisionally registered content feature file is formally registered(step 528).

[0228] By performing the above-mentioned processes, data of the contentfeature file from which the playlist can be generated can be added andinformation on music and CM can be registered, while the time-seriesplaylist is generated.

[0229] As mentioned above, according to the present invention forrecognizing music in real time, broadcasted data on the air (music andthe like used for CM) is digitized and the feature is extracted atintervals of 7.5 seconds, and the feature.is compared with the contentfeature file prepared beforehand, so that the music name can be storedin a storage with information of time when the music is broadcasted asthe time-series list. Accordingly, the time-series playlist can beobtained in which music name, artist name, program (CM), client,product, talent, CD information and the like are included, so thatmeaningful information result can be obtained. This information can beutilized as marketing information for a sales target.

[0230] As for the reason for digitizing the data at intervals of 7.5seconds for extracting the feature, since the time for broadcasting a CMis generally 15 seconds at the minimum currently, a half of 15 secondsis used for the interval for digitizing and extracting feature forperforming search with reliability. Therefore, the time interval fordigitizing can be changed from 7.5 seconds to other value according tothe kind of content.

[0231] In addition, the CMs are conventionally monitored manually forextraction. On the other hand, according to the present invention, itbecomes possible to automatically recognize CMs. In addition, CM data onthe air in TV and FM/AM can be registered without tag information orwatermark information. The CM data can be used for generating thetime-series playlist.

[0232] In addition, according to the present invention, since data inwhich music name and the like can not be determined can be automaticallyregistered in the content generating apparatus in the process forgenerating the time-series playlist, data in the database in the contentgenerating apparatus can be expanded, so that more accurate time-seriesplaylist can be generated.

[0233] The present invention is not limited to the specificallydisclosed embodiments, and variations and modifications may be madewithout departing from the scope of the invention.

1. A playlist generating method for generating a playlist of contentfrom received data, the playlist generating method comprising the stepsof: extracting features of content beforehand, storing the feature in acontent feature file, and storing information relating to the content ina content information DB; extracting features from the received data,and storing the features in a data feature file; searching for contentby comparing data in the content feature file and data in the datafeature file; when the data in the content feature file matches the datain the data feature file, data corresponding to the matched data isstored in a search result file; and generating a playlist for thecontent from the search result file and the content information DB. 2.The playlist generating method as claimed in claim 1, the method furthercomprising the step of, when data in the data feature file is notincluded in the content feature file, registering the data in thecontent feature file.
 3. The playlist generating method as claimed inclaim 2, the method further comprising the steps of: making contentcorresponding to the data that is not included in the content featurefile to be watched or listened to by a person; and registeringinformation relating to the content in the content information DB. 4.The playlist generating method as claimed in claim 1, the method furthercomprising the steps of: when data in the data feature file is notincluded in the content feature file, making content corresponding tothe data to be watched or listened to by a person; adding the content tothe playlist with information related to the content.
 5. A musicrecognizing method for recognizing music from received data, the methodcomprising the steps of: extracting features of music contentbeforehand, storing the features in a content feature file; extractingfeatures from the received data, and storing the features in a broadcastfeature file; searching for music by comparing data in the contentfeature file and data in the broadcast feature file; when a music nameis determined, the music name is stored in a search result file; andgenerating a playlist of music from the search result file.
 6. The musicrecognizing method as claimed in claim 5, the method further comprisingthe steps of: determining whether the received data is music or not; ifthe data is music, storing information indicating that the data is musicand the time when the data is received in a music extracted file; if amusic name for data in the broadcast feature file is not determined inthe step of searching for music, storing the data in a music namenot-extracted file; and generating a music not-detected file from thebroadcast feature file, the music extracted file and the music namenot-extracted file.
 7. The music recognizing method as claimed in claim6, the method further comprising the steps of: making the music storedin the music not-detected file to be listened to by a person; adding amusic name and time of the music stored in the music not-detected filein the playlist.
 8. The music recognizing method as claimed in claim 5,the method comprising the step of generating the time-series playlist byusing the search result file and the content information DB includinginformation associated with the music name, wherein the time-seriesplaylist includes time, a name of music broadcasted at the time andinformation related to the name.
 9. The music recognizing method asclaimed in claim 5, the method comprising the steps of: receivingbroadcasted data in a plurality of areas; sending data received in eacharea to a center system; generating the time-series playlist by usingthe music recognizing method in the center system.
 10. A musicrecognizing method for recognizing music from received data, the methodcomprising the steps of: extracting features of music contentbeforehand, storing the features in a content feature file; receivingbroadcasted data in a plurality of areas; extracting features from thereceived data, and sending the features as data of a broadcast featurefile to a center system in each area; in the center system, searchingfor music by comparing data in the content feature file and data in thebroadcast feature file; if a music name is determined, the music name isstored in a search result file; and generating a playlist of music fromthe search result file.
 11. The music recognizing method as claimed inclaim 8, wherein each of the content information DB and the informationrelated to the music name includes information related to a CM, and theinformation related to the CM in the content information DB isregistered in the content information DB beforehand by the CMrecognizing method, the CM recognizing method further comprising thesteps of: detecting CM data from the received data; extracting featuresof the CM data, and storing the features in the broadcast feature file;performing data comparison between the broadcast feature file and amaster CM content feature file in which features of CM content arestored beforehand; and if data in the broadcast feature file does notexist in the master CM content feature file, registering the data in themaster CM content feature file included in the content information DB asa new CM.
 12. A CM recognizing method for recognizing a CM from receiveddata, and storing recognized CM data, the method comprising the stepsof: detecting CM data from the received data; extracting features of theCM data, and storing the features in a broadcast feature file;performing data comparison between the broadcast feature file and amaster CM content feature file in which features of CM content arestored beforehand; and if data in the broadcast feature file does notexist in the master CM content feature file, registering the data in themaster CM content feature file as a new CM.
 13. The CM recognizingmethod as claimed in claim 12, the step of detecting the CM data fromthe received data comprising the step of detecting a start point and anend point of the CM data, wherein, when the features of the CM data areextracted, a part of the CM data is cut out to a predetermined length,such that a length from the center of the CM data to an end is the sameas a length from the center to another end.
 14. The CM recognizingmethod as claimed in claim 12, the method further comprising the stepsof: displaying CM data that does not exist in the master CM contentfeature file as a result of the data comparison; and registeringinformation relating to the CM data in each database in a CM managementdatabase group including the master CM content feature file.
 15. Aplaylist generating system for generating a playlist of content fromreceived data, the playlist generating system comprising: means forobtaining data in a content feature file that stores features of contentbeforehand, and data in a content information DB that stores informationrelated to the content; means for extracting features from the receiveddata, and storing the features in a data feature file; means forsearching for content by comparing data in the content feature file anddata in the data feature file; means for, if the data in the contentfeature file matches the data in the data feature file, storing datacorresponding to the data in a search result file; and means forgenerating a playlist for the content from the search result file andthe content information DB.
 16. The playlist generating system asclaimed in claim 15, the playlist generating system further comprisingmeans for, if data in the data feature file is not included in thecontent feature file, registering the data of the data feature file inthe content feature file.
 17. The playlist generating system as claimedin claim 16, the system further comprising: means for making contentcorresponding to the data that is not included in the content featurefile to be watched or listened to by a person; and means for registeringinformation corresponding to the content in the content information DB.18. The playlist generating system as claimed in claim 15, the systemfurther comprising: means for, if data in the data feature file is notincluded in the content feature file, making content corresponding tothe data that is not included in the content feature file to be watchedor listened to by a person; adding the content to the playlist withinformation related to the content.
 19. A music recognizing system forrecognizing music from received data, the system comprising: means forobtaining data of a content feature file in which features of musiccontent are stored; means for extracting features from the receiveddata, and storing the features in a broadcast feature file; means forsearching for music by comparing data in the content feature file anddata in the broadcast feature file; means for, if a music name isdetermined, storing the music name in a search result file; and meansfor generating a playlist of music from the search result file.
 20. Themusic recognizing system as claimed in claim 19, the system furthercomprising: means for determining whether the received data is music ornot; means for, if the data is music, storing information indicatingthat the data is music and the time when the data is received in a musicextracted file; means for, if a music name of data in the broadcastfeature file is not determined, storing the data in a music namenot-extracted file; and means for generating a music not-detected filefrom the broadcast feature file, the music extracted file and the musicname not-extracted file.
 21. The music recognizing system as claimed inclaim 20, the system further comprising: means for making the musicstored in the music not-detected file to be listened to by a person;means for adding a music name and time on the music stored in the musicnot-detected file in the playlist.
 22. The music recognizing system asclaimed in claim 19, the system comprising: means for obtaining datafrom a content information DB including information associated with themusic name; means for generating the time-series playlist by using thesearch result file and the content information DB, wherein thetime-series playlist includes time, a name of music broadcasted at thetime and information related to the name.
 23. A music recognizing systemfor recognizing music from received data, the system comprising: aplurality of apparatuses for receiving broadcasted data in a pluralityof areas; a center system for receiving data received in each area fromeach apparatus, the center system comprising: means for obtaining dataof a content feature file in which features of music content is stored;means for extracting features from the received data, and storing thefeatures in a broadcast feature file; means for searching for music bycomparing data in the content feature file and data in the broadcastfeature file; means for, if a music name is determined, storing themusic name in a search result file; and means for generating a playlistof music from the search result file.
 24. A music recognizing system forrecognizing music from received data, the system comprising: a pluralityof apparatuses for receiving broadcasted data and extracting features ofthe broadcasted data in a plurality of areas; a center system forreceiving the features of data received in each area from eachapparatus, the center system comprising: means for obtaining data of acontent feature file in which features of music content is stored; meansfor searching for music by comparing data in the content feature fileand data in the broadcast feature file; means for, if a music name isdetermined, storing the music name in a search result file; and meansfor generating a playlist of music from the search result file.
 25. A CMrecognizing system for recognizing a CM from received data, and storingrecognized CM data, the system comprising: means for detecting CM datafrom the received data; means for extracting features of the CM data,and storing the features in a broadcast feature file; means forperforming data comparison between the broadcast feature file and amaster CM content feature file in which features of CM content arestored beforehand; and means for, if data in the broadcast feature filedoes not exist in the master CM content feature file, registering thedata in the master CM content feature file as a new CM.
 26. The CMrecognizing system as claimed in claim 25, the means for detecting theCM data from the received data comprising means for detecting a startpoint and an end point of the CM data, wherein, when the features of theCM data are extracted, a part of the CM data is cut out to apredetermined length, such that a length from the center of the CM datato an end is the same as a length from the center to another end. 27.The CM recognizing system as claimed in claim 25, the system furthercomprising: means for displaying CM data that does not exist in themaster CM content feature file as a result of the data comparison; andmeans for registering information relating to the CM data in eachdatabase in a CM management database group including the master CMcontent feature file.
 28. A computer readable medium recording programcode for causing a computer to perform processes for generating aplaylist of content from received data, the computer readable mediumcomprising: program code means for extracting features from the receiveddata, and storing the features in a data feature file; program codemeans for obtaining data of a content feature file in which features ofthe content are stored beforehand, and searching for content bycomparing data in the content feature file and data in the data featurefile; program code means for, if the data in the content feature filematches the data in the data. feature file, storing data correspondingto the data in a search result file; and program code means forgenerating a playlist for the content from the search result file andthe content information DB.
 29. The computer readable medium as claimedin claim 28, the computer readable medium further comprising programcode means for, if data in the data feature file is not included in thecontent feature file, registering the data of the data feature file inthe content feature file.
 30. The computer readable medium as claimed inclaim 29, the computer readable medium further comprising: program codemeans for making content corresponding to the data that is not includedin the content feature file to be watched or listened to by a person;and program code means for registering information corresponding to thecontent in the content information DB.
 31. The computer readable mediumas claimed in claim 28, the computer readable medium further comprising:program code means for, if data in the data feature file is not includedin the content feature file, making content corresponding to the datathat is not included in the content feature file to be watched orlistened to by a person; program code means for adding the content tothe playlist with information related to the content.
 32. A computerreadable medium recording program code for causing a computer to performprocesses for recognizing music from received data, the computerreadable medium comprising: program code means for extracting featuresfrom the received data, and storing the features in a broadcast featurefile; program code means for searching for music by comparing data in acontent feature file in which features of music content are stored anddata in the broadcast feature file; program code means for, if a musicname is determined, storing the music name in a search result file; andprogram code means for generating a playlist of music from the searchresult file.
 33. The computer readable medium as claimed in claim 32,the computer readable medium further comprising: program code means fordetermining whether the received data is music or not; program codemeans for, if the data is music, storing information indicating that thedata is music and the time when the data is received in a musicextracted file; program code means for, if a music name of the data inthe broadcast feature file is not determined, storing the data in amusic name not-extracted file; and program code means for generating amusic not-detected file from the broadcast feature file, the musicextracted file and the music name not-extracted file.
 34. The computerreadable medium as claimed in claim 33, the computer readable mediumfurther comprising: program code means for making the music stored inthe music not-detected file to be listened to by a person; program codemeans for adding a music name and time on the music stored in the musicnot-detected file in the playlist.
 35. The computer readable medium asclaimed in claim 32, the computer readable medium comprising: programcode means for obtaining data from a content information DB includinginformation associated with the music name; program code means forgenerating the time-series playlist by using the search result file andthe content information DB, wherein the time-series playlist includestime, a name of music broadcasted at the time and information related tothe name.
 36. A computer readable medium recording program code forcausing a computer to perform processes for recognizing music fromreceived data, the computer readable medium comprising: program codemeans for receiving features of broadcasted data received in each areaas a broadcast feature file from each apparatus; program code means forsearching for music by comparing data in a content feature file in whichfeatures of music content are stored and data in the broadcast featurefile; program code means for, if a music name is determined, storing themusic name in a search result file; and program code means forgenerating a time-series playlist of music from the search result file.37. A computer readable medium recording program code for causing acomputer to perform processes for recognizing a CM from received data,and storing recognized CM data, the computer readable medium comprising:program code means for detecting CM data from the received data; programcode means for extracting features of the CM data, and storing thefeatures in a broadcast feature file; program code means for performingdata comparison between the broadcast feature file and a master CMcontent feature file in which features of CM content are storedbeforehand; and program code means for, if data in the broadcast featurefile does not exist in the master CM content feature file, registeringthe data in the master CM content feature file as a new CM.
 38. Thecomputer readable medium as claimed in claim 37, the program code meansfor detecting the CM data from the received data comprising program codemeans for detecting a start point and an end point of the CM data,wherein, when the features of the CM data are extracted, a part of theCM data is cut out to a predetermined length, such that a length fromthe center of the CM data to an end is the same as a length from thecenter to another end.
 39. The computer readable medium as claimed inclaim 37, the computer readable medium further comprising: program codemeans for displaying CM data that does not exist in the master CMcontent feature file as a result of the data comparison; and programcode means for registering information relating to the CM data in eachdatabase in a CM management database group including the master CMcontent feature file.